• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.501-510
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• 1996

The gas-turbine generator of Seo-Incheon combined-cycle plant was tested for derivation of a model for dynamic analysis. Load rejection and AVR step test was performed to get the dynamic response of generator. The parameters of generator/control system model were determined by these measured data. No-load saturation test was performed for the saturation characteristics of the generator under steady state. V-curve test was also performed so as to find exact generator parameters. Q-axis parameters of generator was derived by measuring power angle. AVR and governor constants have been tuned by their oscillatory period and setting time characteristics. The derived parameters of generator control system is verified by one-machine infinite bus system simulation. (author). 7 refs., 20 figs., 5 tabs.

• Journal of Korea Water Resources Association
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• v.30 no.4
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• pp.327-334
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• 1997

The purpose of this study is to calibrate the parameters of tank model for the derivation of a design flood hydrograph at a certain river basin outlet. The selected stations are Gongju and Naju station which are located in the Keum and the Youngsan river basin, respectively. The results of parameters calibration for tank model are represented a little different values comparing with the proposed values at Gongju station through the verification of flood hydrograph in modeling procedure but the values of tank parameters at Naju station are fitted well for the derivation of flood hydrograph using the proposed design parameters of tank model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.171-176
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• 2009

A rate-sensitive constitutive model was developed, with some simplifying assumptions, in the frame of the standard elastoplastic-viscous relation. The simulations performed using the model were successful for the normally consolidated cohesive soils with the advantage that the parameter values determined at a rate could be used at. different rates. Details on the parameters and additional modification of the model are presented in the successive paper.

• Journal of Drive and Control
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• v.18 no.4
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• pp.43-51
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• 2021

In this study, we designed a hydraulic propulsion propeller system that allows dredged materials to be carried out by the dredger to the disposal place. The proposed model equation was used to formulate the screw propeller specifications considering the resistance to the dredger, and the quantitative specifications of the hydraulic propulsion propeller were determined through the numerical analysis programs. In addition, based on the proposed results, we were able to determine the specifications of the hydraulic system that was used for the hydraulic motor in the propulsion propeller device and then manufactured the hydraulic propulsion propeller. To guarantee the reliability of the proposed model equation, an external testing agency was invited and verified that the hydraulic propulsion propeller based on the proposed model equation could achieve the target speed in the dredger.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.763-774
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• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

• Earthquakes and Structures
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• v.11 no.1
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• pp.141-163
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• 2016

Fiber models have been developed and applied to various structural elements such as shear walls, beams and columns. Only scarcely have fiber models been applied to circular foundation systems such as cast in drilled holes shafts (CIDH). In pile foundations with constraint head boundary conditions, shear deformations can easily contribute to the lateral pile response. However, soil structure interaction formulations such as the p-y method, commonly used for lateral pile design, do not include structural shear deformations in its traditional derivation method. A fiber model that couples shear and axial-bending behavior, originally developed for wall elements was modified and validated on circular cross sections (columns) before being applied to a 0.61 m diameter reinforced concrete (RC) pile with fixed head boundary conditions. The analytical response was compared to measured test results of a fixed head test pile to investigate the possible impact of pile shear deformations on the displacement, shear, and moment profiles of the pile. Results showed that shear displacements and forces are not negligible and suggest that nonlinear shear deformations for RC piles should be considered for fixed-head or similar conditions. Appropriate sensor layout is recommended to capture shear deformation when deriving p-y curves from field measurements.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.1
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• pp.30-36
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• 2023

In this study, an image segmentation model that can evaluate surface porosity based on concrete surface images was derived. Three types of concrete specimens with different water-cement ratios (w/c = 54, 35, and 30%) were prepared, and 2,729 surface images were obtained using an optical microscope. Benchmarking tests, parameter optimization, and final model derivation were performed using the surface images, and an image segmentation model with 97% verification accuracy was obtained. The model was verified by comparing the porosity obtained from the model and X-Ray Microscope (XRM). The model provided similar porosity to that of XRM for the specimens with a high water-cement ratio, but tended to give lower porosity for specimens with a low water-cement ratio.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.529-538
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• 2017

The Ghosh and Kim zero-altered distribution model is used to analyze count data that have too many or too few zeros. The dispersion type parameter ${\delta}$ in the zero-altered distribution model consists of mean, variance and zero probability and has two forms depending on the relation between ${\mu}$ and ${\sigma}^2$. We derived the influence function on ${\delta}$ when ${\sigma}^2{\geq}{\mu}$. To show the validity of the influence function, we used the Census data on the number of births of married women in Korea to compare the estimated changes in ${\delta}$ using this function with those obtained using the direct deletion method. The result proved that the obtained influence function is very accurate in estimating changes in ${\delta}$ when an observation is deleted.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.641-650
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• 2011

Airborne LIDAR system, utilized in various forest studies, provides efficiently spatial information about vertical structures of forest areas. The tree height is one of the most essential measurements to derive forest information such as biomass, which can be estimated from the forest terrain model. As the terrain model is generated by the interpolation of ground points extracted from LIDAR data, filtering methods with high reliability to classify reliably the ground points are required. In this paper, we applied three representative filtering methods to forest LIDAR data with diverse characteristics, measured the errors and performance of these methods, and analyzed the causes of the errors. Based on their complementary characteristics derived from the analysis results, we have attempted to combine the results and checked the performance improvement. In most test areas, the convergence method showed the satisfactory results, where the filtering performance were improved more than 10% in maximum. Also, we have generated DTM using the classified ground points and compared with the verification data. The DTM retains about 17cm RMSE, which can be sufficiently utilized for the derivation of forest information.